Genomic Resources | Kimball Lab

Sequencing and Annotating the Wild Rice Genome

We have been diligently working to develop the first annotated, de novo assembly of the wild rice genome. We have used PacBio and Illumina technologies to generate sequence data as well as HiC and Chicago libraries to aid in the assembly of the genome. Annotation of the genome is currently underway using the transcriptome analysis of six different wild rice tissue types including root, shoot, leaf, seed, female florets, and male florets.

Gaining access to the wild rice genome provides a knowledge base previously unavailable to researchers. This access can 1. Aid in the identification of genes associatied with agronomically-important traits; 2. Help us gain insight into the evolutionary history of wild rice and; 3. Assist in conservation efforts by utilizing conservation genetic approaches- an untapped resource in wild rice that aims to understand the genetic dynamics of a population to avoid extinction and restore biodiversity.

RNA Sequencing

RNA-Seq can be used to define when and how strongly genomic loci are expressed within a cell over time. The current aim for RNA-Seq in the Kimball program is to assess gene expression in NWR as it relates to dormancy. RNA extracted from seeds over a 9-month period, starting post-harvest, will be run through an RNA-Seq workflow to determine when different genomic loci are expressed throughout the dormancy cycle.

Genotyping by Sequencing and SNP Marker Identification

The Kimball program is working to optimize genotyping-by-sequencing (GBS) for use in Northern Wild Rice research. GBS is a type of DNA sequencing that reduces genome complexity to capture and sequence portions of the genome that are most interesting to plant scientists. GBS accomplishes this using restriction enzymes to create smaller fragments of DNA. Restriction enzymes make cuts in strands of DNA at sequences known as genetic palindromes, or sequences that read the same on both the forward and reverse strands. Adapters are then ligated, or joined, onto the “sticky” cut ends of digested fragments and then the fragments are amplified by polymerase chain reaction (PCR), making many copies of the DNA sequence, prior to sequencing.

Sequencing data are delivered in the form of millions of “short reads”. Short reads are strings of nucleotide sequences about 150 bp in length. Using computers, we can rapidly align these sequences to a reference genome and identify single base pair differences called single nucleotide polymorphisms (SNPs) between the reference genome and each of the sequenced samples. A variety of opportunities are provided to researchers with current GBS technologies including its utilization for SNP identification, genetic diversity analyses, genome-wide association studies (GWAS), bulked segregant analysis (BSA), and QTL mapping.

Allele Mining

Allele Mining refers to the process of identifying and using genetic variation that affects a plant's phenotype (the physical manifestation of a trait, such as flower color). NWR is a diploid, which means it has two different copies of each gene. Each of these copies is called an allele and these alleles can have different effects on the plant's phenotype. In cultivated NWR, reduced grain shattering, higher yield, and disease resistance are some examples of desirable traits. Genes controlling these traits are typically identified by their association with genetic markers, such as single nucleotide polymorphisms (SNPs), which are identified using technology such as genotyping-by-sequencing (GBS).

SNPs act as a marker to signal the presence of the gene that it has "tagged", like mile markers on the freeway. The closer the SNP is to the gene of interest, the better. These markers allow us to determine the genomic location(s) affecting a phenotypic trait of interest. Once located, we can attempt to combine alleles of interest from separate individuals using traditional breeding methods.

The Kimball Lab is leveraging modern sequencing and bioinformatic technology to improve genetic resources for NWR. We have generated the first de novo reference assembly of NWR (cultivar Itasca-C12) and genotyped over one thousand individuals to understand the population structure of NWR in its natural habitat and to understand the diversity present in our breeding program.

Comparative Genomics

All life on earth is descended from a common ancestor. Major branches on the tree of life, such as those at the point where plant and animal lineages diverged from each other, occurred in the distant past. The divergence of different plant genera happened in the much more recent past relative to the age of the earth. For example, NWR (Zizania palustris) and white rice (Oryza sativa) are both considered to be “rice” in the broad sense as they are both members of the tribe Oryzeae, but the two genera, Zizania and Oryza last shared a common ancestor approximately 26.7 million years ago. Since the two genera diverged relatively recently from an evolutionary point of view, we expect the two genera to have very similar genomes. On the other hand, 26.7 million years have elapsed since they last shared a common ancestor so there has been sufficient time for differences to accrue.

Other plant species are more distantly related. For example, Brachypodium and sorghum last shared a common ancestor with Zizania/Oryza 42.8 and 54.3 million years ago, respectively. Comparative genomics is the study of similarities and differences between two or more species. At the genome level, we know that O. sativa has 12 chromosomes while Z. palustris has 15 chromosomes. It is hypothesized that the extra three chromosomes are the result of the duplication of chromosomes 1, 4, and 9. We also know that synteny, or the order in which genes occur, is largely conserved between Z. palustris and O. sativa. We are also interested in other genomic elements, such as repeats, that constitute large portions of plant genomes and whether certain gene families are enriched or depleted between species. Genomic resources for Brachypodium, sorghum, and O. sativa are more developed than those for Z. palustris. Using comparative genomics, we can borrow information already known about these other species and apply that knowledge to answer scientific questions about Z. palustris.